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Ferdinand Saussure : le premier cours de linguistique générale : la trilogie achevée : sténogramme Caille, transcription triple, analyses et commentaires
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BLLDB
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UB Frankfurt Linguistik
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Language, Internet and Platform Competition
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In: https://hal.archives-ouvertes.fr/hal-03095655 ; 2020 (2020)
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Learning to scale multilingual representations for vision-language tasks
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BASE
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VAV2 signaling promotes regenerative proliferation in both cutaneous and head and neck squamous cell carcinoma
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BASE
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Controllable Sentence Simplification
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In: LREC 2020 - 12th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-02678214 ; LREC 2020 - 12th Language Resources and Evaluation Conference, May 2020, Marseille, France ; http://www.lrec-conf.org/proceedings/lrec2020/index.html (2020)
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BASE
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Investigating Language Impact in Bilingual Approaches for Computational Language Documentation
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In: Proceedings of the 1st Joint SLTU and CCURL Workshop (SLTU-CCURL 2020), ; SLTU-CCURL workshop, LREC 2020 ; https://hal.archives-ouvertes.fr/hal-02895907 ; SLTU-CCURL workshop, LREC 2020, May 2020, Marseille, France (2020)
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BASE
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French Contextualized Word-Embeddings with a sip of CaBeRnet: a New French Balanced Reference Corpus
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In: CMLC-8 - 8th Workshop on the Challenges in the Management of Large Corpora ; https://hal.inria.fr/hal-02678358 ; CMLC-8 - 8th Workshop on the Challenges in the Management of Large Corpora, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/media/proceedings/Workshops/Books/CMLC-8book.pdf (2020)
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BASE
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Transforming the study of organisms: Phenomic data models and knowledge bases.
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Thessen, Anne E; Walls, Ramona L; Vogt, Lars; Singer, Jessica; Warren, Robert; Buttigieg, Pier Luigi; Balhoff, James P; Mungall, Christopher J; McGuinness, Deborah L; Stucky, Brian J; Yoder, Matthew J; Haendel, Melissa A
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In: PLoS computational biology, vol 16, iss 11 (2020)
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Abstract:
The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model organism databases, genomic data are limited in their scientific impact because they are not accompanied by computable phenomic data. The majority of phenomic data are contained in countless small, heterogeneous phenotypic data sets that are very difficult or impossible to integrate at scale because of variable formats, lack of digitization, and linguistic problems. One powerful solution is to represent phenotypic data using data models with precise, computable semantics, but adoption of semantic standards for representing phenotypic data has been slow, especially in biodiversity and ecology. Some phenotypic and trait data are available in a semantic language from knowledge bases, but these are often not interoperable. In this review, we will compare and contrast existing ontology and data models, focusing on nonhuman phenotypes and traits. We discuss barriers to integration of phenotypic data and make recommendations for developing an operationally useful, semantically interoperable phenotypic data ecosystem.
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Keyword:
Animals; Bioinformatics; Biological; Biological Sciences; Classification; Computational Biology; Databases; Ecosystem; Gene-Environment Interaction; Genetic; Genetics; Human Genome; Humans; Information and Computing Sciences; Knowledge Bases; Mathematical Sciences; Models; Phenomics; Phenotype; Semantics; Statistical
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URL: https://escholarship.org/uc/item/76j2g4bf
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BASE
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History of Logo
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In: Proceedings of the ACM on Programming Languages, vol 4, iss HOPL (2020)
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BASE
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Three-dimensional vocal fold structural change due to implant insertion in medialization laryngoplasty.
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In: PloS one, vol 15, iss 1 (2020)
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BASE
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Differential asthma odds following respiratory infection in children from three minority populations.
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In: PloS one, vol 15, iss 5 (2020)
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BASE
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Differential asthma odds following respiratory infection in children from three minority populations.
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In: PloS one, vol 15, iss 5 (2020)
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BASE
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Joint Neural Models of Word Sense Disambiguation and Machine Translation ; Modèles neuronaux joints de désambiguïsation lexicale et de traduction automatique
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In: https://tel.archives-ouvertes.fr/tel-03027723 ; Informatique et langage [cs.CL]. Université Grenoble Alpes, 2020. Français (2020)
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Joint Neural Models of Word Sense Disambiguation and Machine Translation ; Modèles neuronaux joints de désambiguïsation lexicale et de traduction automatique
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In: https://tel.archives-ouvertes.fr/tel-03033118 ; Intelligence artificielle [cs.AI]. Université Grenoble Alpes [2020-.], 2020. Français. ⟨NNT : 2020GRALM032⟩ (2020)
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Standard-based Lexical Models for Automatically Structured Dictionaries ; Modèles lexicaux standardisés pour les dictionnaires à structure automatique
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In: https://tel.archives-ouvertes.fr/tel-03153438 ; Computation and Language [cs.CL]. Université de Paris, 2020. English (2020)
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Standard-based lexical models for automatically structured dictionnaries ; Modèles lexicaux standardisés pour les dictionnaires à structure automatique
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In: https://tel.archives-ouvertes.fr/tel-03274454 ; Document and Text Processing. Université de Paris, 2020. English. ⟨NNT : 2020UNIP7146⟩ (2020)
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Exploring deep learning techniques in the task of English-Arabic Machine Translation ; Exploration des techniques de l’apprentissage profond au service de la traduction automatique Anglais-Arabe
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In: https://tel.archives-ouvertes.fr/tel-03202829 ; Computation and Language [cs.CL]. Université des Sciences et de la Technologie Houari Boumediene (Algérie), 2020. English (2020)
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A linguistic introduction for machine learning data? ; Une introduction linguistique pour les données de Machine learning?
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In: Humanistica 2020 ; https://hal.archives-ouvertes.fr/hal-02619356 ; Humanistica 2020, Humanistica, May 2020, Bordeaux, France ; http://www.humanisti.ca/colloque2020/ (2020)
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